Machine Learning Insight Into Porous Carbon Materials

Machine Learning Insight Into Porous Carbon Materials Full article

Journal

Computational Materials Science
ISSN: 1879-0801

Output data

Year: 2027, Volume: 276, Article number : 115207, Pages count : 12 DOI: 10.1016/j.commatsci.2026.115207

Tags

Porous carbon materials, Deep learning, Phase-mask prediction, Quasi-three-dimensional construction, Pore structure characterization, Molecular dynamics simulation

Authors

Chubarova Alina A. ¹ , Sergeicheva Darya A. ² , Trenikhin Mikhail V. ¹ , Knyazheva Olga A. ¹ , Lavrenov Aleksandr V. ¹ , Prudnikov Pavel V. ¹

Affiliations

1	Center of New Chemical Technologies BIC, Boreskov Institute of Catalysis, st. Neftezavodskaya, 54, Omsk, 644040, Russia
2	Theoretical Physics Department, Dostoevsky Omsk State University, av. Mira, 55A, Omsk, 644077, Russia

Funding (1)

Ministry of Science and Higher Education of the Russian Federation

FWUR-2024-0039

Chubarova A.A. , Sergeicheva D.A. , Trenikhin M.V. , Knyazheva O.A. , Lavrenov A.V. , Prudnikov P.V.
Machine Learning Insight Into Porous Carbon Materials
Computational Materials Science. 2027. V.276. 115207 :1-12. DOI: 10.1016/j.commatsci.2026.115207 OpenAlex

Submitted:	Aug 2, 2026
Accepted:	Oct 4, 2026
Published online:	Oct 30, 2026

≡ OpenAlex:

W7224791900